An Intelligent Optical Dissolved Oxygen Measurement Method Based on a Fluorescent Quenching Mechanism

Article An Intelligent Optical Dissolved Oxygen Measurement Method Based on a Fluorescent Quenching Mechanism

Fengmei Li, Yaoguang Wei *, Yingyi Chen, Daoliang Li and Xu Zhang

Received: 1 October 2015; Accepted: 1 December 2015; Published: 9 December 2015 Academic Editor: Frances S. Ligler

College of Information and Electrical Engineering, China Agricultural University, 17 Tsinghua East Road, Beijing 100083, China; [email protected] (F.L.); [email protected] (Y.C.); [email protected] (D.L.); [email protected] (X.Z.) * Correspondence: [email protected]; Tel.: +86-10-6273-6764; Fax: +86-10-6273-7741

Abstract: Dissolved oxygen (DO) is a key factor that influences the healthy growth of fishes in aquaculture. The DO content changes with the aquatic environment and should therefore be monitored online. However, traditional measurement methods, such as iodometry and other chemical analysis methods, are not suitable for online monitoring. The Clark method is not stable enough for extended periods of monitoring. To solve these problems, this paper proposes an intelligent DO measurement method based on the fluorescence quenching mechanism. The measurement system is composed of fluorescent quenching detection, signal conditioning, intelligent processing, and power supply modules. The optical probe adopts the fluorescent quenching mechanism to detect the DO content and solves the problem, whereas traditional chemical methods are easily influenced by the environment. The optical probe contains a thermistor and dual excitation sources to isolate visible parasitic light and execute a compensation strategy. The intelligent processing module adopts the IEEE 1451.2 standard and realizes intelligent compensation. Experimental results show that the optical measurement method is stable, accurate, and suitable for online DO monitoring in aquaculture applications.

Keywords: dissolved oxygen; ﬂuorescent quenching; intelligent compensation

1. Introduction Dissolved oxygen (DO) refers to the oxygen molecules dissolved in water and is essential to maintain human and animal life. Oxygen is an important analyte because of its key role in the life science, biotechnology, medicine, and aquaculture industries. The DO content in water is an indication of water quality, and careful control of oxygen levels is important in the self-purification processes of wastewater [1,2]. Water quality is closely related to the contaminants present in water, + such as H2S, NO2, NH4 , and organic matter. Wastewater characteristics, including color, chemical oxygen demand (COD), and biological oxygen demand (BOD), specifically indicate the level of pollutants in industrial wastewater [3]. At the same time, DO plays a very important role in the health and growth of aquatic organisms [4,5]. A DO content of less than 2 mg/L for a certain number of hours causes the suffocation and death of aquatic organisms [6]. For humans, the DO content of drinking water should not be less than 6 mg/L. Consequently, the determination of oxygen concentrations is of high importance in the aquaculture industry and in daily life. However, monitoring the DO content with all its external influencing factors, such as temperature, pressure, and salinity, is difficult. To obtain an accurate DO content, the detection method should implement

Sensors 2015, 15, 30913–30926; doi:10.3390/s151229837 www.mdpi.com/journal/sensors Sensors 2015, 15, 30913–30926 intelligent compensation. In general, three methods can be used to detect DO content: iodometric, electrochemical, and optical methods [7,8]. The iodometric method [9,10] is a popular and precise method of detecting the DO content in water. It is a fiducial method but has a complex detection process and cannot be used to detect the water quality online. This method is mainly used as a benchmark in the laboratory environment (off-line). The electrochemical method [11–14] uses electrodes to detect the current produced by redox reactions at the electrodes. This method can be classified as polarographic type or galvanic cell type based on the detection principle. The electrochemical method has a long history in the detection of DO content; the first so-called Clark polarographic method was designed by Clark of the YSI Company in 1956 [12]. In contrast to iodometry, the electrochemical method monitors DO content by the oxidation-reduction reaction that occurs between the electrode and DO molecules and consumes oxygen in the detection process. Given that instrumental drift is inevitable with the large number of factors that are involved in determining the detection result, electrochemical sensors require regular calibration and replacement. Optical DO sensors [15,16] are more attractive than the iodometry and electrochemical methods because they have a fast response time, do not consume oxygen, have a small drift over time, have the capability to withstand external disturbances, and require marginal calibration. The detection principle of optical DO sensors is based on fluorescent quenching, including fluorescent lifetime detection and fluorescent intensity detection. Intensity detection can be achieved through the photodiode, unlike lifetime, which should be detected based on the phase shift [17]. This study develops an intelligent optical measurement method based on the fluorescent quenching mechanism. The aforementioned methods have some advantages and disadvantages that make them unsuitable to the aquaculture industry in China. First, the detection of DO content is difficult for the aquarist who must deal with numerous factors which influence the aquaculture industry. A comparison of the three methods shows that the electrochemical method is not a good choice because of its weak anti-interference properties. Second, the DO content is not constant, and insufficient concentration in natural water leads to the death of fishes. Thus, detecting DO content in real time is very important. However, iodometry method water samples must be tested in the laboratory, rendering this method unsuitable for monitoring organisms in actual production for this reason. Finally, traditional optical sensors have several disadvantages, including susceptibility to changes in external temperature, pressure, and salinity and attenuation of light source and drift because of the degradation or leaching of the dye. The influence off all these factors can be decreased by adding intelligent processing modules. The conventional optical DO sensor introduced from abroad is expensive and does not have high accuracy when used in the aquaculture industry. Thus, designing and developing an inexpensive and intelligent dedicated optical DO sensor is necessary. This study proposes and develops an intelligent DO measurement method based on the fluorescent quenching mechanism. The sensor contains four modules: fluorescent quenching detection, signal conditioning, intelligent processing, and power supply modules. The sensor based on fluorescent quenching has several advantageous aspects: lower power consumption, smaller size, higher accuracy, and stronger anti-interference properties than iodometry or electrochemical sensors.

2. Materials and Methods

2.1. The Overall Design of Optical Dissolved Oxygen Sensor Given the presence of unstable influencing factors, the sensor adopts an optical probe based on the quenching of fluorescence. Compared with the traditional DO sensor, the intelligent optical DO sensor proposed in this study has an enhanced probe structure and an additional intelligent processing module. These calibration parameters are stored in the transducer electronic data sheet (TEDS) memory. Figure1 shows that the fluorescent quenching detection, signal conditioning, intelligent processing, and power supply modules are included in the intelligent sensor.

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The ﬂuorescent quenching detection module contains a temperature probe and a DO probe. The temperature probe is responsible for collecting the water temperature signals, and the DO probe is responsible for collecting the DO signals. The original input signal can be converted into 0–2.5 V voltageSensors signal 2015, 1 by5, p theage–page signal conditioning circuits. The MSP430 microcontroller, which is the core of the intelligent processing module, is connected to the signal conditioning circuits, TEDS memory, theSensors intel 201ligent5, 15, p ageprocessing–page module, is connected to the signal conditioning circuits, TEDS memory, and serialand serial interface interface [18 ].[18]. The The collected collected datadata are fused fused through through multi multi-probe-probe data data fusion fusion technology technology,, and theandthe DOintelthe DO valueligent value processing obtained obtained ismodule is transferred transferred, is connected through through to compatible the signal conditioningRS485 RS485 interface interface circuits, after after being TEDS being processed memory processed, and analyzedand analyzedserial byinterface theby the microcontroller. [18].microcontroller. The collected The The data RS485 RS485 are interfacefused through allows allows multi the the microcontroller-probe microcontroller data fusion to communicate totechnology communicate, withwith theand upper thethe DOupper PC. value PC. The obtained The sensor sensor is is transferredis powered poweredby bythrough anan on on-off -compatibleoff power power supply, RS485 supply, interfacewhich which is alsoafter is also controlled being controlled processed by the by the MSP430MSP430and microcontroller.analyzed microcontroller. by the microcontroller. The RS485 interface allows the microcontroller to communicate with the upper PC. The sensor is powered by an on-off power supply, which is also controlled by the MSP430 microcontroller.

FigureFigure 1. 1Overall. Overall designdesign of the the optical optical DO DO sensor sensor.. 2.2. Design of the Fluorescent QuenchingFigure 1. O verallDetecti designon Module of the optical DO sensor. 2.2. Design of the Fluorescent Quenching Detection Module 2.2. DesignThe schematic of the Fluorescent of the fluorescent Quenching quenching Detection Module detecti on module is shown in Figure 2. The probe Thehas a schematicn approximate ofthe length fluorescent of 16 cm and quenching a diameter detection of 4 cm. The module compact isshown probe configuration in Figure2. is The used probe has anforapproximate compatibilityThe schematic with length of thethe of fluorescentrequirements 16 cm and quenching of a the diameter aquaculture detecti ofon 4 module cm.industry. The is Asshown compact illustrate in Figure probed in Figure2. configuration The probe2, the is has an approximate length of 16 cm and a diameter of 4 cm. The compact probe configuration is used usedDO for probe compatibility contains dual with high the- requirementsbrightness blue of LEDs, the aquaculture sol-gel film, glass industry. slide, Asred illustrated optical filter, in blue Figure 2, for compatibility with the requirements of the aquaculture industry. As illustrated in Figure 2, the the DOoptica probel filter contains paper, and dual silicon high-brightness photodiode. blue This LEDs, module sol-gel also includes film, glass a platinum slide, red resistance optical to filter, DO probe contains dual high-brightness blue LEDs, sol-gel film, glass slide, red optical filter, blue blue opticalmonitor filterambient paper, temperature and silicon during photodiode. measurement Thiss. The module fluorescent also includes intensity aand platinum temperature resistance are to processedoptical filter in the paper software, and siliconfor temperature photodiode. calibration. This module also includes a platinum resistance to monitormonitor ambient ambient temperature temperature during during measurements. measurements. The The fluorescent fluorescent intensity intensity and and temperature temperature are are processedprocessed in the in softwarethe software for for temperature temperature calibration. calibration.

PCB OF1

PCB Temperature Probe BOluFe1 Reference LED Silicon Photodiode Temperature Probe Blue Reference BluLeE EDx citation Silicon Photodiode LED OF3 Blue Excitation LED OF3 OF2 Metal Case

OF2 Metal CGaslaess Slide Sol-Gel Film

Glass Slide Sol-Gel Film Figure 2. Schematic of the fluorescence quenching detection module. The dual highFigure-Figurebrightness 2. Schematic2. Schematic blue ofLEDs of the the (LA470 ﬂuorescence fluorescence-02) are quenching quenching modulated detecti detection aton the module module.same. frequency, so that the reference LED can be used to compensate the excitation LED because the light intensity loss of The dual high-brightness blue LEDs (LA470-02) are modulated at the same frequency, so that Thethe blue dual LED high-brightnesss are exactly the blue same. LEDs At the (LA470-02) same frequency, are modulated the photodiode at the can same reduce frequency, background so that the reference LED can be used to compensate the excitation LED because the light intensity loss of the referenceradiation LEDdue to can the beambient used light to compensate in the measurement the excitation environment LED becauseand avoid the the light excitation intensity of any loss of the blue LEDs are exactly the same. At the same frequency, the photodiode can reduce background the bluefluorescen LEDst arematerial. exactly In theaddition, same. the At intensity the same of frequency,the LEDs are the reduced photodiode to a low can level reduce at which background the photobleachingradiation due to phenomenonthe ambient light of thein the dye measurement has a small environment probability andof occurring avoid the [19]. excitation The centralof any radiation due to the ambient light in the measurement environment and avoid the excitation of any wavelengthfluorescent material.of the blue In excitationaddition, theLED intensity is about of 465 the nm, LEDs which are reducedis filtered to by a lowa blue level bandpass at which filter the ﬂuorescent material. In addition, the intensity of the LEDs are reduced to a low level at which paperphotobleaching to screen out phenomenon the light of ofother the wavelengths. dye has a small The experimental probability resultsof occurring show that[19]. the The blue central light wavelength of the blue excitation LED is about 465 nm, which is filtered by a blue bandpass filter paper to screen out the light of other wavelengths. The experimental results show that the blue light 309153

3 Sensors 2015, 15, 30913–30926 the photobleaching phenomenon of the dye has a small probability of occurring [19]. The central wavelength of the blue excitation LED is about 465 nm, which is filtered by a blue bandpass filter paper to screen out the light of other wavelengths. The experimental results show that the blue light can induce the sensitive membrane to emit fluorescence at 650 nm. To reduce the influence of parasitic light, the probe is equipped with blue bandpass filter papers (OF1 and OF2) in front of the LEDs and red high-pass filter (OF3) in front of the silicon photodiode. A silicon photodiode (OPT 301) is used to receive the fluorescence emitted from the sol-gel film and blue light from the reference LED. The blue excitation LED and blue reference LED are separated on different sides of the red high-pass filter, which is beneficial in cutting off parasitic light and guaranteeing the accuracy of the optical signal detection. The fluorescent sensing film is the most important part of the DO sensor and its performance significantly influences the accuracy, efficiency, and stability of the sensor. Researchers have conducted several studies on fluorescence indicators [20–22] and found that the most common fluorescent indicators contain metal porphyrin complexes, organic polycyclic aromatic hydrocarbons, and transition metal complexes [23]. Ru(bpy)3Cl2 has been chosen as the fluorescence indicator in this study because of its highly emissive metal-to-ligand charge-transfer state, long lifetime, and strong absorption in the blue-green region of the spectrum, which is compatible with the high-brightness blue LED [20]. The dye is entrapped in a porous and hydrophobic sol-gel film that is approximately 0.04 mm. The sol-gel film is mounted on the glass slide surface, which should be transparent for the excitation and luminescence to penetrate. The film should also be in the shape of an arc and maintain a stable size; the arc surface is designed to increase the area of contact and avoid surface bubble. The operating principle of the sensor is based on the fluorescent quenching mechanism. The fluorescent quenching process is described by the Stern-Volmer equation [24–26]:

F 0 “ 1 ` K rQs (1) F sv where:

F0 denotes the ﬂuorescence signal intensity of anaerobic water; F denotes the ﬂuorescence signal intensity of the water samples;

KSV denotes the Stern-Volmer constant; and [Q] denotes the concentration of quencher.

As the equation shows, the degree of ﬂuorescent quenching F0/F has a straight-line relationship with the concentration of the quencher [Q]. In this system, the quencher is the DO, so the DO content can be determined by using Equation (1).

2.3. Design of the Signal Conditioning Module The block diagram of the intensity measurement system is shown in Figure3. The signal conditioning module is responsible for collecting and processing the information. The dual LEDs are modulated (MOD) into on-off at a frequency of 20 kHz. LED1 induces the sol-gel film to emit red fluorescence. At the same time, LED2 emits blue light as a contrast. The luminescence signal from the sensor dyes arrives time-delayed at the single photodiode (because of the luminescence lifetime of the dye), so that the reference and luminescence signals are detected in different time windows without interference. The fluorescence signal from the photodiode is converted to a voltage signal via an I/V switching circuit. The signal is then amplified (AMP) to obtain a voltage signal of 0–2.5 V and eliminate the higher harmonics of the signal. The voltage signal is filtered by a low pass (LP) filter and provides a voltage signal proportional to the measured intensity shift. Finally, the output voltage is divided by the voltage value based on the intensity in the anaerobic water to obtain F0/F, which has a linear correlation with the DO content. As presented in the Stern-Volmer equation, the DO content can be determined.

30916 Sensors 2015, 15, 30913–30926 Sensors 2015, 15, page–page

Pt LED2

Sensors 2015, 15, page–page RS485 OF1 MOD Sensitive MCU membrane PD Pt LELDE2D1 TEDS RS485 OF2 OF1 OF3 MOD Sensitive MCU membrane PD LP amp LED1 I/V TEDS OF2 OF3 FigureFigure 3. Schematic 3. Schematic of of the the signal signal conditioning conditioning module module.. amp I/V 2.4. Design of the Intelligent ProcessingLP Module 2.4. Design of the Intelligent Processing Module With the rapid development of computers, communications, and networks, the DO sensor Figure 3. Schematic of the signal conditioning module. Withshould the be rapid more development intelligent, networked of computers,, and integrated communications, [20]. To solve and the networks, problems of the traditional DO sensor shouldoptical be more sensor intelligent,s, the intelligent networked, optical DO and sensor integrated proposed [20 in]. this To study solve is thedeveloped problems with of automatic traditional 2.4. Design of the Intelligent Processing Module opticalcompensation sensors, thes intelligent, which are opticalsuitable DOfor the sensor online proposed detection inof thisaquaculture study is over developed long periods with. automatic compensations,With the which rapid are development suitable for of the computer online detections, communicatio of aquaculturens, and network over longs, the periods. DO sensor shouldIEEE1451.2 be more Standard intelligent, networked, and integrated [20]. To solve the problems of traditional optical sensors, the intelligent optical DO sensor proposed in this study is developed with automatic IEEE1451.2The Standard data transfer is implemented using the protocols described in IEEE 1451.2 [27,28]. The compensations, which are suitable for the online detection of aquaculture over long periods. Theintelligent data transfer sensor is includes implemented a smart using transducer the protocols interface moduledescribed (STIM) in IEEE and 1451.2 network [27 capable,28]. The application processor (NCAP), and the sensor provides a general interface standard and a TEDS intelligentIEEE1451.2 sensor Standard includes a smart transducer interface module (STIM) and network capable standard format for the intelligent sensor and the field bus. NCAP is connected to the STIM through application processor (NCAP), and the sensor provides a general interface standard and a TEDS an RS485The data interface, transfer as shownis implemented in Figure 4. using the protocols described in IEEE 1451.2 [27,28]. The standardintelligent formatThe calibration sensor for the includes intelligent parameters a smart sensor are transducer stored and the in ﬁeld the interface TEDS bus. NCAPmodule as shown is (STIM) connected in Fig andure tonetwork4. the Through STIM capable these through an RS485applicationparameters, interface, processor the as shown original (NCAP), in signals Figure and 4the can. sensor been provide converteds a general into corrected interface signals,standard including and a TEDS DO, Thestandardtemperature calibration format, pressure, for parameters the intelligentsalinity, and are sensor lu storedminous and the influx field the signa bus. TEDSls. NCAP as is shown connected in to Figure the STIM4. through Through thesean parameters, RS485 interface, the as original shown in signals FigDure(1) can D4. (2) been D ( n ) converted into corrected signals, including DO, i j p temperature,The pressure, calibrationfXXX( salinity, parameters1 , 2 ,... andn )  luminous are stored  ... ﬂux in CXHXHXHthe signals. i , j ... pTEDS [ 1  as 1 ] [shown 2  2 in ] ...[ Figure n  4. n ] Through these(2) parameters, the original signals i can0 j  0 been p  0 converted into corrected signals, including DO, Dp q Dp q Dpnq temperatureIn the equation, pressure,, X salinityn denotes, and1 the lu 2sensorminous output flux signavariablesls. ; Hn denotes the revised output variables; i j p Dn denotesf p theX1, orderX2, ... ofX noutputq “ variablesD(1) D (2)... ; and D ( n )C Cii,j,…,p,j...pr denotesX1 ´ H 1thes r Xpolynomial2 ´ H2s ... rcoefficient.Xn ´ Hns (2) i j p fXXX(1 , 2 ,...ni )“0j“0 p ...“ 0 CXHXHXH i , j ... p [ 1  1 ] [ 2  2 ] ...[ n  n ] (2) ÿ iÿ0 j  0ÿ p  0

In theIn equation, the equationXn, denotesXn denotes the the sensor sensor output output variables;variables; HHn ndenotesdenotes the the revised revised output output variables variables;; Dn denotesDn denotes the orderthe order of outputof output variables; variables; and and CCii,j,…,p,j,..., pdenotesdenotes the the polynomial polynomial coefficient. coefﬁcient.

Figure 4. Model of data correction.

The calibration standard equation is shown in Figure 4. The relationship between the output variables and revised output variables, such as DO, temperature, pressure, salinity , and luminous FigureFigure 4. 4.Model Model ofof5 data correction correction..

The calibration standard equation is shown in Figure 4. The relationship between the output variables and revised output variables, such as DO, temperature, pressure, salinity, and luminous 5 30917 Sensors 2015, 15, 30913–30926

SensorsThe 2015 calibration, 15, page–page standard equation is shown in Figure4. The relationship between the output variables and revised output variables, such as DO, temperature, pressure, salinity, and luminous flux signalsflux signa arels converted are converted into ainto standard a standard form. form The. sensor The sensor can directly can directly determine determine accurate accurate values values when itwhen uses it the uses calibration the calibration parameters parameters stored in stored the TEDS, in the which TEDS not, which only facilitates not only automatic facilitates recognition automatic butrecognition also solves but thealso sensor solves automatic the sensor correction automatic problem. correction In prob thelem intelligent. In the opticalintelligent DO optical sensor, DO the total,sensor, channel, the total, and channel calibration, and TEDScalibration must TEDS be defined. must Inbe thisdefin study,ed. In the this definition study, the of definition total and channel of total TEDSand channel makes the TEDS intelligent makes the optical intelligent DO sensor optical more DO standardized, sensor more and standard that ofized the, calibration and that of TEDS the maycalibration correct TEDS theoriginal may cor datarect the at anyoriginal time. data These at any functions time. These have functions significance have for significance the maintenance for the andmaintenance diagnosis and of thediagnosis sensors of [ 29the,30 sensors]. Thus, [29 the,30]. intelligent Thus, the optical intelligent DO optical sensor isDO called sensor a “plugis called and a play”“plug device.and play” device.

3. Experiment Experimentss and and Discussion Discussionss

3.1.3.1. Calibration and Validation 3.1.1. Temperature Compensation of the Optical DO Sensor 3.1.1. Temperature Compensation of the Optical DO Sensor The temperature dependence of the oxygen sensor has a number of contributions, including the The temperature dependence of the oxygen sensor has a number of contributions, including the temperature dependence of the fluorescence sensing film, light source, and the diffusion coefficient temperature dependence of the fluorescence sensing film, light source, and the diffusion coefficient in the water. As discussed in Section 2.2, the light intensity related to temperature is measured by in the water. As discussed in Section 2.2, the light intensity related to temperature is measured by the the probe, and the temperature effect is measured by the sensor based on the thermistor [31]. This probe, and the temperature effect is measured by the sensor based on the thermistor [31]. This study study designs a correction model based on the temperature applicable to online DO monitoring. This designs a correction model based on the temperature applicable to online DO monitoring. This model can perform temperature compensation to reduce the influence of temperature through the model can perform temperature compensation to reduce the influence of temperature through the curve fitting algorithm. curve fitting algorithm. To eliminate the influence of temperature on sensitive film and light, anaerobic water and To eliminate the influence of temperature on sensitive film and light, anaerobic water and oxygen saturated solutions are prepared as standard solutions, which are heated with an integrated oxygen saturated solutions are prepared as standard solutions, which are heated with an integrated thermostatic magnetic blender (HWCL-1) from 0 ˝C to 40 ˝C in an off-light environment. The values thermostatic magnetic blender (HWCL-1) from 0 °C to 40 °C in an off-light environment. The values are measured by a commercial DO meter (YSI 6150) in steps of 5 ˝C (0–40 ˝C), and the data between are measured by a commercial DO meter (YSI 6150) in steps of 5 °C (0–40 °C ), and the data between output signal and temperature obtained are displayed in the plot shown in Figure5. output signal and temperature obtained are displayed in the plot shown in Figure 5.

Figure 5.5. LLineine chart of the DO content and output voltage signal.signal.

The relationship can bebe describeddescribed byby thethe followingfollowing equations:equations:

 DOtt1 1 1 U DOt1 “ β1 ` βt1U DOt 22 U $ DOt2 “ β2 ` βt t22U (3) (3) ’  . ’  . & DOtn n tn U DOtn “ βn ` βtnU ’ The slope is an important parameter’ to achieve the DO content, which changes with %’ temperature. The relationship between the slope and temperature can be obtained based on the curve fit method in this study. As shown in Fig30918ure 6, the slope of the output voltage signal can be fitted by Equation (4):

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The slope is an important parameter to achieve the DO content, which changes with temperature. The relationship between the slope and temperature can be obtained based on the curve fit method in this study. As shown in Figure6, the slope of the output voltage signal can be fitted by Equation (4): Sensors 2015, 15, page–page 2 3 4 5 βt “ α0 ` α1T ` α2T ` α3T ` α4T ` α5T (4)    TTTTT  2   3   4   5 t 0 1 2 3 4 5 (4) In the equation, α0 = 52.488, α1 = ´4.3436, α2 = 0.2157, α3 = ´0.0061, α4 = 0.00008, In the equation, α20 = 52.488, α1 = −4.3436, α2 = 0.2157, α3 = −0.0061, α4 = 0.00008, α5 = −0.0000004, α5 = ´0.0000004, and R = 0.9998, as seen in Figure6, which denotes a very good linear fitting. The DO 2 contentand R = can 0.9998 be obtained, as seen in at Fig anyure temperature, 6, which denotes taking a Equation very good (4) linear into Equationfitting. The (3), DO and content Equation can (5)be canobtained then be at achieved. any temperature, taking Equation (4) into Equation (3), and Equation (5) can then be achieved. 2 3 4 5 DOt “ β ` α0U ` α1UT ` α2UT 2` α3UT 3` α4UT 4` α 55UT (5) DOt   0 U   1 UT   2 UT   3 UT   4 UT   5 UT (5)

Figure 6.6. FittingFitting curve of the slope.slope.

The calibration standard Equation (2) in the TEDS calibration can be adapted as follows: The calibration standard Equation (2) in the TEDS calibration can be adapted as follows: 15 ij DOt1 5 C ij[][] U  H12  T  H (6) ij00 i j DOt “ CijrU ´ H1s ¨ rT ´ H2s (6) i“ j“ If H1 = 0 and H2 = 0, then Equationÿ (6)0 ÿcan0 be presented by Equation (7): 2 3 4 5 If H1 = 0 and H2 = 0, thenDOt Equation C00  CTCT 01 (6)  can 02 be  presented CT 03  CT 04 by Equation CT 05 (7): (7) CU  CUT  CUT2  CUT 3  CUT 4  CUT 5 10 11 122 133 144 15 5 DOt “ C00 ` C01T ` C02T ` C03T ` C04T ` C05T 2 3 4 5 (7) The calibration value`C10sU are` C consistent11UT ` C12 withUT the` C actual13UT temperature` C14UT ` Cand15UT output voltage. The DO value must be corrected according to the real-time temperature. Taking C00 = β, C00 − C05 = 0,C10 = α0, C11 =The α1, C calibration12 = α2, C13 values= α3, C are14 = consistentα4, and C15 with = α5 theinto actual Equation temperature (7) and detecting and output the voltage.temperature The and DO valueoutput must voltage, be correctedthe accurate according DO value to can the be real-time determined temperature. in the 0–40 Taking °C range C00 =(i.e.β,,C the00 range´ C05 of= the 0, Csensor).10 = α0 The,C11 temperature= α1,C12 = probeα2,C13 in= thisα3 ,Csensor14 = αcan4, andtrack C 15the= temperatureα5 into Equation response (7) andof the detecting DO sensor the ˝ temperaturein real time, and thereby output achieving voltage, thetemperature accurate DO compensation value can be in determined an application in the where 0–40 frequentC range (shorti.e., the-term range changes of the in sensor). temperature The occur temperature. The calibration probe in curve this sensor based can on intensity track the measurement temperature responsechanges because of the DO of sensor the impacts in realof time, typical thereby drift achieving sources, including temperature the compensation leaching of the in indicator, an application LED whereoutput frequent, and ageing short-term of the changessol-gel matrix in temperature. Thus, the occur. sensor The require calibrations recalibration curve based after on a intensity certain measurementperiod, but the changes frequency because achieve ofsthe much impactsof more progress typical than drift the sources, electrochemical including thesensor. leaching In addition, of the indicator,the temperature LED output, compensation and ageing should of the be sol-gel processed matrix. in the Thus, shade the to sensor avoid requires the influence recalibration of daylight after aand certain background period, butfluorescence. the frequency achieves much more progress than the electrochemical sensor. In addition, the temperature compensation should be processed in the shade to avoid the inﬂuence of daylight3.1.2. Pressure and background Compensation ﬂuorescence. of the Optical DO Sensor Given that the DO value increases when the sol-gel film is moderately affected by pressure, the pressure affects the accuracy of the measurement. Pressure compensation is needed in the measurement of oxygen, and the correction formula30919 [32] is as follows: P DO  C * (8) S 101.3

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3.1.2. Pressure Compensation of the Optical DO Sensor Given that the DO value increases when the sol-gel ﬁlm is moderately affected by pressure, the pressure affects the accuracy of the measurement. Pressure compensation is needed in the measurement of oxygen, and the correction formula [32] is as follows:

Sensors 2015, 15, page–page P DO1 “ C ˚ (8) S 101.3 In the equation, DO’ denotes the DO in the pressure of P; CS denotes the normal atmospheric In the equation, DO1 denotes the DO in the pressure of P; C denotes the normal atmospheric pressure value; and P denotes the actual atmospheric pressure value.S pressure value; and P denotes the actual atmospheric pressure value. CS can be obtained through the national standard table at different temperatures. At different CS can be obtained through the national standard table at different temperatures. At different temperature,temperature, the theaqueous aqueous solution solutionss are are subjected subjected to differentdifferent pressures. pressures. As As mapped mapped in Figurein Figure7, the 7, the experimentexperiment shows shows that that the the optical optical DO DO sensor sensor introduced introduced inin this this study study can can effectively effectively eliminate eliminate the the effecteffect of pressure of pressure and and that that the the pressure pressure compensation compensationhas has a a good good effect. effect.

FigureFigure 7 7.. PressurePressure compensation test. test.

3.1.3.3.1.3. Salinity Salinity Compensation Compensation of ofthe the Optical Optical DO DO Sensor GivenGiven that that the the solubility solubility of of oxygen in in water water decreases decrease ass the as salt the content salt content increases, increases the DO must, the DO mustbe be compensated compensated according according to theto the salinity. salinity. When When the salinitythe salinity (i.e., expressed(i.e., expressed as the as total the salinity) total salinity) is is belowbelow 35 35 ppt ppt,, the the correction correction formulaformula [ 32[32]] is is given given by: by:

2 DODO “ CCSSS´ n n∆ C CS (9) (9)

In theIn equation, the equation, DO”DO denotes” denotes the theDO DO value value at a at salinity a salinity of n of; C n;S denotesCS denotes the the DO DO value value in inpure pure water; n denoteswater; then denotes salinity the value; salinity and value; ΔCS denotes and ∆CS thedenotes reduction the reduction of DO according of DO according to salinity to salinity (1 ppt) (1. ppt). CS andCS andΔCS ∆canCS canbe obtained be obtained through through the the national national standard table table at at different different temperatures. temperatu Theres. The + 2´ aqueousaqueous solution solution is measured is measured u usingsing KCl, KCl, NHNH44+, andand COCO3 32− asas ionsions in in the the experiment. experiment The. T ionhe densityion density of theof themeasure measurementment solutions solutions is is between between 0 and 0 and 40 ppt. 40 Theppt. DO The values DO measuredvalues measure separatelyd s areeparately shown are shownon on the the basis basis of the of experimentalthe experimental data in data Figure in 8Figure. The analysis 8. The ofanalysis the data of shows the data that shows the DO that values the DO have certain effects when ionic strength regulators are added. The experiment shows that the optical values have certain effects when ionic strength regulators are added. The experiment shows that the sensor satisﬁes the salinity compensation in the aquatic environment. The salinity compensation optical sensor satisfies the salinity compensation in the aquatic environment. The salinity parameters are also stored in the calibration TEDS. compensation parameters are also stored in the calibration TEDS.

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Figure 8. Salinity compensation test.

3.1.4. Excitation LED Compensation The experimental results show that different intensities of the excitation LED have a large influence on the fluorescence intensity of the sensitive film. The intelligent processing module also allows for the adjustment of the calibration parameters to correct the excitation blue LED at the time of measurement (i.e., if this differs from the excitation at the time of calibration). The luminous flux 8 Sensors 2015, 15, page–page

In the equation, DO’ denotes the DO in the pressure of P; CS denotes the normal atmospheric pressure value; and P denotes the actual atmospheric pressure value. CS can be obtained through the national standard table at different temperatures. At different temperature, the aqueous solutions are subjected to different pressures. As mapped in Figure 7, the experiment shows that the optical DO sensor introduced in this study can effectively eliminate the effect of pressure and that the pressure compensation has a good effect.

Figure 7. Pressure compensation test.

3.1.3. Salinity Compensation of the Optical DO Sensor Given that the solubility of oxygen in water decreases as the salt content increases, the DO must be compensated according to the salinity. When the salinity (i.e., expressed as the total salinity) is below 35 ppt, the correction formula [32] is given by:

DO  CSS  n  C (9)

In the equation, DO” denotes the DO value at a salinity of n; CS denotes the DO value in pure water; n denotes the salinity value; and ΔCS denotes the reduction of DO according to salinity (1 ppt). CS and ΔCS can be obtained through the national standard table at different temperatures. The aqueous solution is measured using KCl, NH4+, and CO32− as ions in the experiment. The ion density of the measurement solutions is between 0 and 40 ppt. The DO values measured separately are shown on the basis of the experimental data in Figure 8. The analysis of the data shows that the DO values have certain effects when ionic strength regulators are added. The experiment shows that the

Sensorsoptical2015 sensor, 15, 30913–30926 satisfies the salinity compensation in the aquatic environment. The salinity compensation parameters are also stored in the calibration TEDS.

Figure 8.8. Salinity compensation test.test.

3.1.4.3.1.4. Excitation LED Compensation The experimental results show that different intensitintensitiesies of the excitation LED have a large influenceinfluence on the fluorescencefluorescence intensityintensity ofof thethe sensitivesensitive film.film. The intelligent processing module also allows for the adjustment of the calibration parameters to correct the excitation blue LED at the time of measurement (i.e.i.e.,, if this differs fromfrom thethe excitationexcitation atat thethe timetime ofof calibration).calibration). The luminous flux flux attenuation curve of the blue LED shows a similar8 exponential form at 100 ˝C. When the service time reaches about 10,000 h, the luminous flux of the blue LED (L470-02) drops to about 70% of the original luminous flux. Thus, when the LEDs work beyond 10,000 h, the sensor probe must be replaced. Before replacement, illuminant compensation is required to guarantee the accuracy of the DO sensor. The experimental results show that this sensor can effectively compensate the effect of the light source caused by the instability or aging of the light source. The compensation formula is shown in the following equation, and the calibration parameters are also stored in the TEDS. When the intensity of the reference blue LED changes, Equation (8) is used to correct the intensity value of fluorescence quenched by oxygen:

eα eβ Eδ “ Eγ ¨ p0.7 ď ď 1q (10) eβ eα

In the equation, eα denotes the original intensity value of the reference LED; eβ denotes the measured intensity value of the reference LED; Eγ denotes the measured intensity value of the quenched fluorescence; and Eδ denotes the corrected intensity value of the quenched fluorescence. The long-term stability of the sensor in aquaculture tank water has been continuously studied for over 12 months. With the passage of time, the sol-gel matrix is prone to losing its original features, which may cause drifts in calibration, leaching, and bleaching of the dye. As described above, if the intensity of the fluorescence declines (i.e., after about 12 months), then the sensor probe should be replaced rather than the whole sensor device with the separate structure.

3.2. Analysis of the Performance of the Sensor To verify the performance of the sensor, the optical DO sensor is tested in terms of our aspects: accuracy, stability, precision, repeatability, rapidity. Its superior performance proves that the intelligent optical DO sensor can be used to monitor the DO content in the aquaculture industry. The experimental processes are shown below.

3.2.1. Accuracy Test In the laboratory, the room temperature is about 25 ˝C, and three groups of standard aqueous solutions are measured: 5.02, 9.98, and 18.03 mg/L. The deﬁned oxygen contents are adjusted by mixing the oxygen and nitrogen with mass ﬂow controllers. The sample contents are checked using a commercial DO meter. Compared with reference values, the experimental data in Table1 show that

30921 Sensors 2015, 15, 30913–30926

the relative error is less than ˘2%, the measurement error is less than 0.2 mg/L, and the resolution of the optical DO sensor is 0.01 mg/L within the range of 0–20 mg/L, which conforms to the accuracy requirements. At the same time, the temperature error is less than 0.5 ˝C, which shows that the temperature probe is accurate.

Table 1. Accuracy test.

Measurements Absolute Relative Samples AVG 1 2 3 4 5 6 7 8 Error Error 5.02 4.86 4.79 4.89 4.93 4.89 4.91 5.09 4.98 4.92 0.1 1.99% 9.98 10.12 10.09 10.21 9.89 10.06 9.91 9.89 10.13 10.04 0.06 0.60% 18.03 17.85 17.83 17.91 17.87 17.96 17.87 17.93 18.03 17.91 0.12 0.67%

3.2.2. Stability Test The response of the optical sensor appears to be stable within the measurement error, which meets the speciﬁed stability requirement of 0.2 mg/L. In the laboratory, the DO content is measured withinSensors 201 125, h15 in, page steps–page of 1 h. The standard aqueous solution is adjusted by mixing the oxygen and nitrogen with mass ﬂow controllers. The experimental results are 2.51, 5.58, 7.22, 10.01, 14.56, and18.12 18.12 mg/L. mg/L. As shown As shown in Fig inure Figure 9, 9the, the largest largest error error is is less less than 0.02 0.02 mg/L,mg/L, which which meets meets the the requirements ofof thethe opticaloptical dissolveddissolved oxygenoxygen sensor.sensor.

Figure 9.9. StabilityStability test.test.

3.2.3.3.2.3. Precision Test Precision refers to the discrete degree of the values that are repeatedly measured by the same method underunder the the same same experimental experimental conditions condition fors the for same the sample. same sample Generally,. Generally the relative, the standard relative deviationstandard deviation (RSD) is used (RSD) to is explain used to the explain sensor the precision. sensor precision The RSD. T indicateshe RSD indicates that the results that the are results more concentrated.are more concentrated. The standard The solution standard contains solution Na 2containsSO3, and Na this2SO sample3, and is this continuously sample is measured continuously ten times.measur Theed ten measurement times. The resultsmeasurement are shown results in Table are shown2. The micro-controllerin Table 2. The m calculatesicro-controller the RSD calculate everys tenthe measurements,RSD every ten indicatingmeasurements that, theindicating precision that of thisthe precision group of dataof this is verygroup good of data when is thevery RSD good is lesswhen than the 2%. RSD The is less micro-controller than 2%. The inputs micro these-controller data into inputs the internalthese data memory. into the As internal shown memory. in Figure 10As, theshown results in Figure show that10, the the results sensor show has a that high the precision. sensor has a high precision.

Table 2. Precision test.

AVG Sample 1 2 3 4 5 6 7 8 9 10 Average RSD average A 5.56 5.62 5.60 5.44 5.49 5.51 5.50 5.82 5.71 5.60 5.59 1.97%

B 9.96 9.91 9.89 10.22 10.15 10.04 10.00 9.98 10.02 10.15 10.03 1.10%

C 18.90 18.85 18.86 18.74 18.69 3092218.56 18.74 18.63 18.60 18.59 18.73 0.64%

Figure 10. Precision test.

10 Sensors 2015, 15, page–page

18.12 mg/L. As shown in Figure 9, the largest error is less than 0.02 mg/L, which meets the requirements of the optical dissolved oxygen sensor.

Figure 9. Stability test.

3.2.3. Precision Test Precision refers to the discrete degree of the values that are repeatedly measured by the same method under the same experimental conditions for the same sample. Generally, the relative standard deviation (RSD) is used to explain the sensor precision. The RSD indicates that the results are more concentrated. The standard solution contains Na2SO3, and this sample is continuously measured ten times. The measurement results are shown in Table 2. The micro-controller calculates the RSD every ten measurements, indicating that the precision of this group of data is very good when the RSD is less than 2%. The micro-controller inputs these data into the internal memory. As shown in Figure 10, the results show that the sensor has a high precision. Sensors 2015, 15, 30913–30926 Table 2. Precision test.

Table 2. Precision test. AVG Sample 1 2 3 4 5 6 7 8 9 10 Average RSD AVG Average average Sample 1 2 3 4 5 6 7 8 9 10 RSD A 5.56 5.62 5.60 5.44 5.49 5.51 5.50 5.82 5.71 average5.60 5.59 1.97%

B A9.96 5.569.91 5.629.89 5.60 5.4410.22 5.4910.15 5.51 10.04 5.50 5.8210.00 5.719.98 5.60 10.02 5.5910.15 1.97%10.03 1.10% B 9.96 9.91 9.89 10.22 10.15 10.04 10.00 9.98 10.02 10.15 10.03 1.10% C 18.90C 18.9018.8518.85 18.86 18.86 18.7418.74 18.6918.69 18.56 18.56 18.74 18.6318.74 18.6018.63 18.59 18.60 18.7318.59 0.64%18.73 0.64%

FigureFigure 10.10. PrecisionPrecision test.test.

3.2.4. Repeatability Test

Na2SO3 is added into the aqueous solutions10 to achieve the sample solutions (i.e., 2.51, 9.24, and 12.57 mg/L). The sensor is used to measure the DO values of the sample solutions. The data are recorded every hour and continuously measured ten times. Table3 shows that the relative error is less than 2%. The result of the data analysis indicate that the repeatability meets the requirements of the optical DO sensor.

Table 3. Stability test.

Measurement Results Samples Relative Error 1 2 3 4 5 6 7 8 9 10 2.51 2.54 2.5 2.44 2.56 2.62 2.48 2.63 2.55 2.59 2.63 1.59% 9.24 9.22 9.19 9.16 9.13 9.33 9.25 9.23 9.22 9.16 9.13 0.43% 12.51 12.49 12.44 12.45 12.44 12.67 12.71 12.58 12.55 12.49 12.51 0.16%

3.2.5. Speed Test

Two cups of water are prepared in laboratory. 5% Na2SO3 and a suitable amount of CoCl2 are added to one of them. They are placed in the air for two days to ensure that both temperatures are same, which can eliminate the inﬂuence of temperature on the measurement results. Series A indicates the change of DO content from tap water to anaerobic water, and the Series B line indicates the change from anaerobic water to tap water. From Figure 11, we can see that the response time is less than 3 min. After 1 min, the Series A is nearly 0 mg/L. However, the response time of Series B is about 3 min. The reason of this phenomenon is that the process of ﬂuorescence quenching must achieve dynamic balance. Series B should take some time to react, but it doesn’t need time in anaerobic water. The data indicates that detection response speed meets the requirements of the optical DO sensor.

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3.2.4. Repeatability Test

Na2SO3 is added into the aqueous solutions to achieve the sample solutions (i.e., 2.51, 9.24, and 12.57 mg/L). The sensor is used to measure the DO values of the sample solutions. The data are recorded every hour and continuously measured ten times. Table 3 shows that the relative error is less than 2%. The result of the data analysis indicate that the repeatability meets the requirements of the optical DO sensor.

Table 3. Stability test.

Measurement Results Relative Samples 1 2 3 4 5 6 7 8 9 10 Error 2.51 2.54 2.5 2.44 2.56 2.62 2.48 2.63 2.55 2.59 2.63 1.59% 9.24 9.22 9.19 9.16 9.13 9.33 9.25 9.23 9.22 9.16 9.13 0.43% 12.51 12.4 12.44 12.45 12.44 12.67 12.71 12.58 12.55 12.49 12.51 0.16% 9 3.2.5. Speed Test

Two cups of water are prepared in laboratory. 5% Na2SO3 and a suitable amount of CoCl2 are added to one of them. They are placed in the air for two days to ensure that both temperatures are same, which can eliminate the influence of temperature on the measurement results. Series A indicates the change of DO content from tap water to anaerobic water, and the Series B line indicates the change from anaerobic water to tap water. From Figure 11, we can see that the response time is less than 3 min. After 1 min, the Series A is nearly 0 mg/L. However, the response time of Series B is about 3 min. The reason of this phenomenon is that the process of fluorescence quenching must achieve dynamic balance. Series B should take some time to react, but it doesn’t needSensors time2015 , in15 , 30913–30926anaerobic water. The data indicates that detection response speed meets the requirements of the optical DO sensor.

Figure 11. Speed Test. Figure 11. Speed Test.

3.2.6. On-Site Verification Test 3.2.6. On-Site Veriﬁcation Test Figure 12 is the real-time graph of dissolved oxygen changes in aquaculture ponds. After Figure 12 is the real-time graph of dissolved oxygen changes in aquaculture ponds. After sunrise, sunrise, phytoplankton produces photosynthesis, which releases a large amount of oxygen. The phytoplankton produces photosynthesis, which releases a large amount of oxygen. The increase of increase of oxygen is more than the consumption, so the DO content gradually increases. Over a oxygen is more than the consumption, so the DO content gradually increases. Over a period of time, period of time, at the peak of photosynthesis, DO content is at a maximum. After sunset, the at the peak of photosynthesis, DO content is at a maximum. After sunset, the phytoplankton undergo phytoplankton undergo respiration which consumes oxygen instead of photosynthesis. In addition, respiration which consumes oxygen instead of photosynthesis. In addition, with the respiration with the respiration of aquatic animals, DO content decreases rapidly. After all night, the Sensorsofaquatic 2015, 15, p animals,age–page DO content decreases rapidly. After all night, the accumulation is reduced to accumulation is reduced to a minimum at dawn. These changes perfectly accord with the test data, a minimum at dawn. These changes perfectly accord with the test data, which proved that the which proved that the developed DO sensor has a reliable performance. In contrast to change rates of developedoxygen consumed DO sensor by hasorganism a reliables, the performance. temperature In has contrast little toinfluence change rates on DO of oxygen content consumed in the on-bysite organisms, test. the temperature has little inﬂuence11 on DO content in the on-site test.

FigureFigure 12. 12.On-On-sitesite Test Test..

4. Conclusions 4. Conclusions To detect the dissolved oxygen content exactly in aquaculture industry applications, an To detect the dissolved oxygen content exactly in aquaculture industry applications, an intelligent optical dissolved oxygen measurement method based on a fluorescent quenching intelligent optical dissolved oxygen measurement method based on a fluorescent quenching mechanism has been designed in this paper. The advantages of the unique sensor head based on mechanism has been designed in this paper. The advantages of the unique sensor head based fluorescent quenching have been highlighted and intensity measuring circuits and intelligent on fluorescent quenching have been highlighted and intensity measuring circuits and intelligent processing have been described. With the optical dissolved oxygen sensor probe in the paper, the processing have been described. With the optical dissolved oxygen sensor probe in the paper, the detection of dissolved oxygen became more accurate and interference-free. In view of the influence detection of dissolved oxygen became more accurate and interference-free. In view of the influence of temperature, pressure, salinity and blue excitation LED on measurement, this paper has designed of temperature, pressure, salinity and blue excitation LED on measurement, this paper has designed an intelligent processing module. The accurate DO content can be achieved by the intelligent optical DO sensor with the correction coefficients stored in the calibration TEDS. The experiments have shown that the sensor performance can meet the30924 specifications for the monitoring DO content in aquaculture industry, such as low-power consumption, fast response, ability to detect online, high accuracy and strong stability, which will enable reliable operation for periods of months at the very least. In addition, the use of an optical measurement method and the intelligent calibration technique could be applicable in other medical and environmental monitoring areas.

Acknowledgments: Funds for this research was supported by “Special Fund for Agro-scientific Research in the Public Interest”, Modern Fishery Digitization and Integration & Demonstration of Internet of Things Technology (201203017).

Author Contributions: Study concept and design: Yaoguang Wei, Daoliang Li and Yingyi Chen; data acquisition: Fengmei Li and Xu Zhang; statistical analysis: Xu Zhang and Fengmei Li; writing of the manuscript: Fengmei Li and Xu Zhang; study supervision: Daoliang Li, Yaoguang Wei and Yingyi Chen.

Conflicts of Interest: The authors declare no conflict of interest.

References

12 Sensors 2015, 15, 30913–30926 an intelligent processing module. The accurate DO content can be achieved by the intelligent optical DO sensor with the correction coefﬁcients stored in the calibration TEDS. The experiments have shown that the sensor performance can meet the speciﬁcations for the monitoring DO content in aquaculture industry, such as low-power consumption, fast response, ability to detect online, high accuracy and strong stability, which will enable reliable operation for periods of months at the very least. In addition, the use of an optical measurement method and the intelligent calibration technique could be applicable in other medical and environmental monitoring areas.

Acknowledgments: Funds for this research was supported by “Special Fund for Agro-scientific Research in the Public Interest”, Modern Fishery Digitization and Integration & Demonstration of Internet of Things Technology (201203017). Author Contributions: Study concept and design: Yaoguang Wei, Daoliang Li and Yingyi Chen; data acquisition: Fengmei Li and Xu Zhang; statistical analysis: Xu Zhang and Fengmei Li; writing of the manuscript: Fengmei Li and Xu Zhang; study supervision: Daoliang Li, Yaoguang Wei and Yingyi Chen. Conflicts of Interest: The authors declare no conflict of interest.

References

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